Richard Zemel
Richard Zemel
Professor of Computer Science, University of Toronto
Verified email at - Homepage
Cited by
Cited by
Show, attend and tell: Neural image caption generation with visual attention
K Xu, J Ba, R Kiros, K Cho, A Courville, R Salakhudinov, R Zemel, ...
International conference on machine learning, 2048-2057, 2015
Prototypical networks for few-shot learning
J Snell, K Swersky, RS Zemel
arXiv preprint arXiv:1703.05175, 2017
Skip-thought vectors
R Kiros, Y Zhu, R Salakhutdinov, RS Zemel, A Torralba, R Urtasun, ...
arXiv preprint arXiv:1506.06726, 2015
Siamese neural networks for one-shot image recognition
G Koch, R Zemel, R Salakhutdinov
ICML deep learning workshop 2, 2015
Gated graph sequence neural networks
Y Li, D Tarlow, M Brockschmidt, R Zemel
arXiv preprint arXiv:1511.05493, 2015
Fairness through awareness
C Dwork, M Hardt, T Pitassi, O Reingold, R Zemel
Proceedings of the 3rd innovations in theoretical computer science …, 2012
The helmholtz machine
P Dayan, GE Hinton, RM Neal, RS Zemel
Neural computation 7 (5), 889-904, 1995
Multiscale conditional random fields for image labeling
X He, RS Zemel, MA Carreira-Perpinán
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision …, 2004
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Y Zhu, R Kiros, R Zemel, R Salakhutdinov, R Urtasun, A Torralba, S Fidler
Proceedings of the IEEE international conference on computer vision, 19-27, 2015
Autoencoders, minimum description length, and Helmholtz free energy
GE Hinton, RS Zemel
Advances in neural information processing systems 6, 3-10, 1994
Unifying visual-semantic embeddings with multimodal neural language models
R Kiros, R Salakhutdinov, RS Zemel
arXiv preprint arXiv:1411.2539, 2014
Learning fair representations
R Zemel, Y Wu, K Swersky, T Pitassi, C Dwork
International conference on machine learning, 325-333, 2013
Information processing with population codes
A Pouget, P Dayan, R Zemel
Nature Reviews Neuroscience 1 (2), 125-132, 2000
Understanding the effective receptive field in deep convolutional neural networks
W Luo, Y Li, R Urtasun, R Zemel
Proceedings of the 30th International Conference on Neural Information …, 2016
Multimodal neural language models
R Kiros, R Salakhutdinov, R Zemel
International conference on machine learning, 595-603, 2014
Generative moment matching networks
Y Li, K Swersky, R Zemel
International Conference on Machine Learning, 1718-1727, 2015
Exploring models and data for image question answering
M Ren, R Kiros, R Zemel
arXiv preprint arXiv:1505.02074, 2015
Inference and computation with population codes
A Pouget, P Dayan, RS Zemel
Annual review of neuroscience 26 (1), 381-410, 2003
Meta-learning for semi-supervised few-shot classification
M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ...
arXiv preprint arXiv:1803.00676, 2018
Probabilistic interpretation of population codes
RS Zemel, P Dayan, A Pouget
Neural computation 10 (2), 403-430, 1998
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